Unsupervised learning of digit recognition using spike-timing-dependent plasticity

In order to understand how the mammalian neocortex is performing computations, two things are necessary; we need to have a good understanding of the available neuronal processing units and mechanisms, and we need to gain a better understanding of how those mechanisms are combined to build functioning systems. Therefore, in recent years there is an increasing interest in how spiking neural networks (SNN) can be used to perform complex computations or solve pattern recognition tasks. However, it remains a challenging task to design SNNs which use biologically plausible mechanisms (especially for learning new patterns), since most such SNN architectures rely on training in a rate-based network and subsequent…

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  Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

  Awards: 200021-143337, 143337, 200021-, 200021